Apparatus and method for detecting obstacle

ABSTRACT

An apparatus and method for detecting an obstacle include a camera to photograph first and second images at different points in time successively. A calculator is configured to calculate a movement distance and a rotation amount of a vehicle by comparing the two images photographed by the camera with each other. A rotation amount compensator is configured to compensate for the rotation amount of the first image based on the second image. A difference value calculator is configured to calculate a difference value between the first image of which the rotation amount is compensated for and the second image based on the calculated movement distance of the vehicle. An obstacle detector extracts a region having the difference value exceeding an expectation value to detect the obstacle.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority to Korean PatentApplication No. 10-2013-0101733, filed on Aug. 27, 2013 in the KoreanIntellectual Property Office, the disclosure of which is incorporatedherein in its entirety by reference.

TECHNICAL FIELD

The present disclosure relates to an apparatus and method for detectingan obstacle, and more particularly, to a technology of detecting anobstacle using a difference value between two images.

BACKGROUND

Generally, in a technology of detecting an obstacle of a vehicle, anultrasonic sensor provided in the vehicle is used. However, theultrasonic sensor may erroneously sense the obstacle depending on aposition at which it is mounted and the surrounding environment. Inaddition, in the case of detecting the obstacle using the ultrasonicsensor, a place at which the obstacle is not present is sensed by errordue to a prominence or depression of the ground or disturbance of asound source, such that an erroneous alarm may be issued. Therefore,reliability for detecting the obstacle is decreased.

Further, in the case of detecting the obstacle using the ultrasonicsensor, the obstacle may be detected only in a direction in which theultrasonic sensor is mounted. That is, in order to detect the obstaclein all directions of the vehicle, ultrasonic sensors need to be mountedin all directions of the vehicle.

SUMMARY

The present disclosure has been made to solve the above-mentionedproblems occurring in the prior art while advantages achieved by theprior art are maintained intact.

An aspect of the present disclosure provides an apparatus and method fordetecting an obstacle capable of detecting the obstacle around a vehicleby identifying a bottom surface using a difference value depending onvehicle movement between top-view images photographed at differentpoints in time.

According to an exemplary embodiment of the present disclosure, anapparatus for detecting an obstacle includes a camera configured tophotograph first and second images at different points in time amongsuccessively photographed images. A calculator is configured tocalculate a movement distance and a rotation amount of a vehicle bycomparing the two images photographed by the camera with each other. Arotation amount compensator compensates for a rotation amount of thefirst image based on the second image. A difference value calculator isconfigured to calculate a difference value between the first image ofwhich the rotation amount is compensated for and the second image basedon the calculated movement distance of the vehicle. An obstacle detectorextracts a region having a difference value exceeding an expectationvalue to detect the obstacle.

The difference value calculator may move a reference image in a specificpixel unit and determine a relationship equation of the difference valuedepending on a pixel movement amount based on an average value in eachblock in each moved pixel unit.

The difference value calculator may convert the movement distance of thevehicle depending on controller area network (CAN) information into apixel value in the image to calculate the pixel movement amount andapply the calculated pixel movement amount to the determinedrelationship equation to calculate the expectation value for thedifference value.

The apparatus for detecting an obstacle may further include a mapper tomap the difference value calculated from the first image and the secondimage and a magnitude of a speed field between the first image and thesecond image to each other.

The obstacle detector may identify a region having the same speed andthe difference value corresponding to the movement of the vehicle fromthe difference value and the magnitude of the speed field mapped to eachother as a bottom surface.

The calculator may convert the pixel value in the image from a region inwhich the vehicle is positioned up to a region in which a magnitude of aspeed field exceeds the expectation value into a unit distance tocalculate a distance up to the obstacle.

The calculator may calculate the movement distance and the rotationamount of the vehicle between the two images using the controller areanetwork (CAN) information of the vehicle, wherein the CAN informationincludes at least one of a radius of a vehicle wheel, a circumference ofthe wheel, the number of sawteeth of a rear wheel, a pulse value of thewheel depending on a difference between the two images and a steeringvalue.

The first and second images may be a top-view image.

According to another exemplary embodiment of the present disclosure, amethod for detecting an obstacle includes obtaining first and secondimages at different points in time. A movement distance and a rotationamount of a vehicle are calculated by comparing the first and secondimages with each other. The rotation amount of the first image iscompensated for based on the second image. A difference value iscalculated between the first image of which the rotation amount iscompensated for and the second image based on the calculated movementdistance of the vehicle. The difference value calculated from the firstimage and the second image and a magnitude of a speed field between thefirst image and the second image are mapped to each other. The obstaclefrom a region having a difference value exceeding an expectation valueis detected based on the difference value and the magnitude of the speedfield.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, features, and advantages of the presentdisclosure will be more apparent from the following detailed descriptiontaken in conjunction with the accompanying drawings.

FIG. 1 is a block diagram showing a configuration of an apparatus fordetecting an obstacle according to an exemplary embodiment of thepresent disclosure.

FIGS. 2 to 10B are illustrative diagrams for describing an operation ofthe apparatus for detecting an obstacle according to an exemplaryembodiment of the present disclosure.

FIG. 11 is a flow chart showing an operation flow of a method fordetecting an obstacle according to an exemplary embodiment of thepresent disclosure.

DETAILED DESCRIPTION

Hereinafter, exemplary embodiments of the present disclosure will bedescribed with reference to the accompanying drawings.

FIG. 1 is a block diagram showing a configuration of an apparatus fordetecting an obstacle according to an exemplary embodiment of thepresent disclosure. Referring to FIG. 1, the apparatus for detecting anobstacle according to an exemplary embodiment of the present includes asignal processor 110, a camera 120, an output 130, a memory 140, acalculator 150, a rotation amount compensator 160, a difference valuecalculator 170, a mapper 180, and an obstacle detector 190. Here, thesignal processor 110 controls a signal flow between the respective unitsof the apparatus for detecting an obstacle.

The camera 120, which photographs images around the vehicle, may bedisposed at the front, the rear, the left, and the right of the vehicle.The camera 120 can successively photograph first and second imagesaround the vehicle at different points in time. Here, it is assumed thatthe first image is an image photographed before the second image isphotographed, and the second image is an image photographed after thefirst image is photographed. The first and second images correspond to atop-view image in which the front, rear, left, right images of thevehicle are synthesized with each other. The first and second images maybe formed by synthesizing the front, rear, left, right images of thevehicle photographed by the camera 120 with each other andview-converting the synthesized images. A vehicle having an around-viewmonitoring (AVM) system may also provide the top-view image.

The output 130, which outputs an operation state and an obstacledetection result of the apparatus for detecting an obstacle in thevehicle, may be a monitor, a navigation screen, or a speaker and abuzzer.

The memory 140 may store an operation value of the apparatus fordetecting an obstacle and store the images obtained from the camera 120.

The calculator 150 calculates a movement distance and a rotation amountof the vehicle depending on a difference between the first and secondimages by comparing the first and second images with each other. Here,the calculator 150 may calculate the movement distance and the rotationamount of the vehicle between two images using controller area network(CAN) information of the vehicle. In other words, the calculator 150 maycalculate the movement distance L of the vehicle using a radius R of awheel of the vehicle, a circumference 2ΠR of the wheel, the number N ofsawteeth of a rear wheel, and a pulse value P of the wheel depending onthe movement of the vehicle between two images, as shown in FIG. 2.

When the movement distance L of the vehicle between the two images iscalculated using the CAN information, it may be calculated by thefollowing [Equation 1].

L=P*2ΠR/N   [Equation 1]

The calculator 150 may calculate the rotation amount of the vehicleusing a steering value depending on the movement of the vehicle betweenthe two images.

In addition, the calculator 150 may calculate the distance from thevehicle to the obstacle detected in the image. In this case, thecalculator 150 converts a pixel value in the image from a region inwhich the vehicle is positioned up to a region in which the obstacle isdetected into a unit distance of each pixel, thereby making it possibleto calculate the distance to the obstacle.

The rotation amount compensator 160 compensates for a rotation amount ofthe obtained image using the rotation amount of the vehicle calculatedby the calculator 150. In this case, the rotation amount compensator 160compensates for a rotation amount of the first image based on the secondimage. An example thereof will be described in more detail withreference to FIGS. 3A to 4B.

The difference value calculator 170 moves a reference image of thetop-view image obtained from the camera 120 in a specific pixel unit anddetermines a relationship equation of the difference value depending ona pixel movement amount based on an average value in each block in eachmoved pixel unit. An example thereof will be described in more detailwith reference to FIGS. 5A to 6.

Here, the difference value calculator 170 converts the movement distanceof the vehicle between the first and second images into the pixel valuein the image to calculate the pixel movement amount and applies thecalculated pixel movement amount to the relationship equation asdescribed above to calculate an expectation value for the differencevalue.

In addition, the difference value calculator 170 calculates thedifference value between the first image of which the rotation amount iscompensated for by the rotation amount compensator 160 and the secondimage, based on the movement distance of the vehicle between the firstand second images calculated by the calculator 150. The difference valuebetween the first image of which the rotation amount is compensated forand the second image may be a magnitude of an optical flow, but is notlimited thereto. However, in the following exemplary embodiment, adescription will be provided on the assumption that the difference valuebetween the first image of which the rotation amount is compensated for,and the second image is the magnitude of the optical flow.

The mapper 180 maps the difference value calculated from the first andsecond images and a magnitude of a speed field between the first andsecond images to each other. In this case, the obstacle detector 190 maydetect an obstacle region from an image in which the calculateddifference value and the magnitude of the speed field are mapped to eachother.

In other words, the obstacle detector 190 identifies a region having thesame speed and the difference value corresponding to the movement of thevehicle from the difference value and the magnitude of the speed fieldmapped to each other as a bottom surface. In addition, the obstacledetector 190 extracts a region in which the difference value calculatedbetween the first and second images exceeds an expectation value andrecognizes the extracted region in which the obstacle is present.Further, the obstacle detector 190 recognizes a region in which themagnitude of the speed field exceeds a reference value as a region inwhich the obstacle is present.

Therefore, the obstacle detector 190 detects the region in which theobstacle is present as the obstacle, and the output 130 outputs anobstacle detecting result. In this case, the calculator 150 may convertthe pixel value in the image from the region in which the vehicle ispositioned up to the region where the magnitude of the speed fieldexceeds the reference value into a unit distance to calculate a distanceto the obstacle. In this case, the output 130 outputs information on thecalculated distance to the obstacle.

FIGS. 2 to 10B are illustrative diagrams for describing an operation ofthe apparatus for detecting an obstacle according to an exemplaryembodiment of the present disclosure.

As FIG. 2 shows an example of a rear wheel, when it is assumed that aradius R of a wheel of the vehicle is 0.33436 m, and the number N ofsawteeth of a rear wheel is 47, L=0.045P by the above Equation 1. Whenthe pulse value P of the wheel depending on the movement of the vehiclebetween the two images obtained from the CAN information is substitutedinto the above Equation 1, L may be easily calculated.

FIG. 3A shows an original image of the first image, and FIG. 3B shows anoriginal image of the second image. FIG. 4A shows the first image ofwhich a rotation amount is compensated for, and FIG. 4B shows anoriginal image of the second image.

As shown in FIGS. 3A and 3B, in the case in which the vehicle isrotated, a difference is generated in all of the remaining regionsexcept for the vehicle in the first and second images, which has aneffect on the difference value. Therefore, as shown in FIGS. 3A and 3B,when the difference value depending on the movement of the vehiclebetween the two images is calculated without compensating for therotation amount of the first image, a larger error may be generated ascompared with an actual movement amount of the vehicle.

On the other hand, as shown in FIGS. 4A and 4B, when the vehicle isrotated, and the rotation amount of the first image is compensated forbased on a neighboring region of the second image, since positions of afixed obstacle or a bottom surface around the vehicle between the twoimages coincide with each other, the difference value depending on themovement of the vehicle may be more accurately calculated as comparedwith FIGS. 3A and 3B.

FIGS. 5A to 5F show difference values depending on a pixel movementamount, and FIG. 6 shows a relationship graph of the difference valuedepending on the pixel movement amount from FIG. 5.

The apparatus for detecting an obstacle according to an exemplaryembodiment of the present disclosure moves the reference image in thespecific pixel unit and calculates the difference value depending on thepixel movement amount based on an average value in each block in eachmoved pixel unit. FIGS. 5A to 5F show an image obtained by moving thereference image in a 5 px unit.

FIG. 5A shows an image obtained by moving the reference image by 5 px,where a difference value Vxi is 4.6928. FIG. 5B shows an image obtainedby moving the reference image by 10 px, where a difference value Vxi is8.9629. FIG. 5C shows an image obtained by moving the reference image by15 px, where a difference value Vxi becomes 13.6205. FIG. 5D shows animage obtained by moving the reference image by 20 px, where adifference value Vxi is 18.0932. FIG. 5E shows an image obtained bymoving the reference image by 25 px, where a difference value Vxibecomes 22.8412. FIG. 5F shows an image obtained by moving the referenceimage by 30 px, where a difference value Vxi becomes 20.8990.

The pixel movement amounts and the difference values in FIGS. 5A to 5Fmay be represented by a graph of FIG. 6. As shown in FIG. 6, the pixelmovement amounts and the difference values are represented by a lineargraph, through which a relationship equation between the pixel movementamount and the difference value may be determined. Therefore, theapparatus for detecting an obstacle may convert the movement distance ofthe vehicle depending on the CAN information into the pixel value in theimage to calculate the pixel movement amount and apply the calculatedpixel movement amount to the determined relationship equation tocalculate an expectation value for the difference value.

FIGS. 7A to 10B show difference values and speed fields depending onvehicle movement between two images obtained around the vehicle.

Referring to FIGS. 7A, 8A, 9A, and 10A showing the difference valuesdepending on the vehicle movement between the two images, a differencevalue where the obstacle is positioned may be larger than a differencevalue where the obstacle is not present.

Referring to FIGS. 7B, 8B, 9B, and 10B showing the magnitude of thespeed fields depending on the vehicle movement between the two images, amagnitude of a speed field where the obstacle is positioned may belarger than that of a speed field where the obstacle is not present,similar to the difference value.

An operation flow of the apparatus for detecting an obstacle accordingto an exemplary embodiment of the present disclosure configured asdescribed above will be described below in more detail.

FIG. 11 is a flow chart showing an operation flow of a method fordetecting an obstacle according to an exemplary embodiment of thepresent disclosure. As shown in FIG. 11, the apparatus for detecting anobstacle according to an exemplary embodiment of the present disclosureobtains the first and second images at different points in time (S100),calculates the movement distance and the rotation amount of the vehiclebetween the two images obtained in S100 (S110), and compensates for therotation amount of the first image based on the second image dependingon the rotation amount calculated in S110 (S120).

The apparatus for detecting an obstacle according to an exemplaryembodiment of the present disclosure calculates an expectation value ofthe difference value depending on the movement distance of the vehiclein the corresponding image using a relationship equation depending onthe pixel movement amount and the difference value (S130) and calculatesthe difference value depending on the difference between the two imagesobtained in S100 (S140).

Then, the apparatus for detecting an obstacle according to an exemplaryembodiment of the present disclosure compares the difference valuecalculated in S140 and the expectation value calculated in S130 witheach other, extracts a region in which the calculated difference valueexceeds the expectation value (S150), and detects the obstacle from theregion extracted in S150 (S160). The apparatus for detecting an obstacleaccording to an exemplary embodiment of the present disclosure outputsthe obstacle detecting result in S160 through an output 130 so as to beconfigured by a user (S170).

According to an exemplary embodiment of the present disclosure, thebottom surface and the obstacle around the vehicle are detected usingthe difference value depending on the movement of the vehicle betweenthe top-view images photographed at different points in time, therebyminimizing an error in detecting the bottom surface and the obstacle dueto erroneous sensing of the sensor and detecting the obstacle in alldirections of the vehicle.

Although the apparatus and the method for detecting an obstacleaccording to the exemplary embodiment of the present disclosure havebeen described with reference to the accompanying drawings, the presentdisclosure is not limited to the exemplary embodiment and theaccompanying drawings disclosed in the present specification, but may bemodified without departing from the scope and spirit of the presentdisclosure.

What is claimed is:
 1. An apparatus for detecting an obstacle,comprising: a camera to photograph first and second images at differentpoints in time successively; a calculator configured to calculate amovement distance and a rotation amount of a vehicle by comparing thetwo images photographed by the camera with each other; a rotation amountcompensator to compensate for a rotation amount of the first image basedon the second image; a difference value calculator configured tocalculate a difference value between the first image of which therotation amount is compensated for and the second image based on thecalculated movement distance of the vehicle; and an obstacle detector toextract a region having the difference value exceeding an expectationvalue between the first image of which the rotation amount iscompensated for and the second image to detect the obstacle.
 2. Theapparatus for detecting an obstacle according to claim 1, wherein thedifference value calculator moves a reference image in a specific pixelunit and determines a relationship equation of the difference valuedepending on a pixel movement amount based on an average value in eachblock in each moved pixel unit.
 3. The apparatus for detecting anobstacle according to claim 2, wherein the difference value calculatorconverts the movement distance of the vehicle depending on controllerarea network (CAN) information into a pixel value in the image tocalculate the pixel movement amount and applies the calculated pixelmovement amount to the determined relationship equation to calculate theexpectation value for the difference value.
 4. The apparatus fordetecting an obstacle according to claim 1, further comprising a mapperconfigured to map the difference value calculated from the first imageof which the rotation amount is compensated for and the second image anda magnitude of a speed field between the first image of which therotation amount is compensated for and the second image to each other.5. The apparatus for detecting an obstacle according to claim 4, whereinthe obstacle detector identifies a region having the same speed and thedifference value corresponding to the movement of the vehicle from thedifference value and the magnitude of the speed field mapped to eachother as a bottom surface.
 6. The apparatus for detecting an obstacleaccording to claim 3, wherein the calculator converts the pixel value inthe image from a region in which the vehicle is positioned up to aregion in which a magnitude of a speed field exceeds the expectationvalue into a unit distance to calculate a distance up to the obstacle.7. The apparatus for detecting an obstacle according to claim 1, whereinthe calculator calculates the movement distance and the rotation amountof the vehicle between the two images using controller area network(CAN) information of the vehicle, the CAN information including at leastone of a radius of a vehicle wheel, a circumference of the wheel, anumber of sawteeth of a rear wheel, a pulse value of the wheel dependingon the vehicle movement between the two images, and a steering value. 8.The apparatus for detecting an obstacle according to claim 1, whereinthe first and second images are top-view images.
 9. A method fordetecting an obstacle, comprising: obtaining first and second images atdifferent points in time; calculating a movement distance and a rotationamount of a vehicle by comparing the first and second images with eachother; compensating for the rotation amount of the first image based onthe second image; calculating a difference value between the first imageof which the rotation amount is compensated for and the second imagebased on the calculated movement distance of the vehicle; mapping thedifference value calculated from the first image of which the rotationamount is compensated for and the second image and a magnitude of aspeed field between the first image of which the rotation amount iscompensated for and the second image to each other; and detecting theobstacle from a region having the difference value exceeding anexpectation value based on the difference value and the magnitude of thespeed field.